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Impact of seasonal variability of sea waves on the dynamics of a predator–prey system

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Abstract

In this work, a predator–prey model has been proposed to study the impact of sea wave on the system dynamics. Since the predation success of predator species is inextricably related with the amount of sea wave, so a predation efficiency function of wave flow has been introduced in the model system. The well-posedness of the proposed system has been established by proving the positivity, boundedness, and persistence properties. All the equilibrium points have been found along with their parametric conditions of existence. The local stability analysis of all the equilibrium points and global stability analysis of the interior equilibrium point have been studied. Both the analysis of trans-critical bifurcation and Hopf-bifurcation have been performed in a systematic way. It can be seen from the model analysis that the stability of the system dynamics is greatly influenced by both the wave and conversion rate parameters. Additionally, the wave parameter has an immense impact on the population densities of both species. Furthermore, a non-autonomous version of the suggested model system has been created by using the wave flow parameter as a time-dependent periodicity function to take into account the seasonality phenomenon. It has been discovered that the seasonally-forced system exhibits a wide spectrum of dynamical scenarios including bursting phenomenon in the system dynamics. All of the analytical results have been supported suitably by extensive numerical simulations.

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Data sharing is not applicable to this article as no new data were created or analyzed in this study.

References

  1. J.F. Andrews, A mathematical model for the continuous culture of microorganisms utilizing inhibitory substrates. Biotechnol. Bioeng. 10(6), 707–723 (1968)

    Article  Google Scholar 

  2. I. Hanski, The Functional Response of Predators: Worries About Scale (1991)

  3. C.S. Holling, The components of predation as revealed by a study of small-mammal predation of the European pine sawfly1. Can. Entomol. 91(5), 293–320 (1959)

    Article  Google Scholar 

  4. C.S. Holling, Some characteristics of simple types of predation and parasitism1. Can. Entomol. 91(7), 385–398 (1959)

    Article  Google Scholar 

  5. P.A. Braza, The bifurcation structure of the Holling–Tanner model for predator-prey interactions using two-timing. SIAM J. Appl. Math. 63(3), 889–904 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  6. C. Cosner, D.L. DeAngelis, J.S. Ault, D.B. Olson, Effects of spatial grouping on the functional response of predators. Theoret. Popul. Biol. 56(1), 65–75 (1999)

    Article  MATH  Google Scholar 

  7. D. Xiao, S. Ruan, Global analysis in a predator-prey system with nonmonotonic functional response. SIAM J. Appl. Math. 61(4), 1445–1472 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  8. M. Fan, Y. Kuang, Dynamics of a nonautonomous predator-prey system with the Beddington–Deangelis functional response. J. Math. Anal. Appl. 295(1), 15–39 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  9. S. Gakkhar, R.K. Naji, Seasonally perturbed prey-predator system with predator-dependent functional response. Chaos Solitons Fractals 18(5), 1075–1083 (2003)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  10. R. Arditi, L.R. Ginzburg, Coupling in predator-prey dynamics: ratio-dependence. J. Theor. Biol. 139(3), 311–326 (1989)

    Article  ADS  Google Scholar 

  11. H. Freedman, R. Mathsen, Persistence in predator-prey systems with ratio-dependent predator influence. Bull. Math. Biol. 55(4), 817–827 (1993)

    Article  MATH  Google Scholar 

  12. X. Wang, L. Zanette, X. Zou, Modelling the fear effect in predator-prey interactions. J. Math. Biol. 73(5), 1179–1204 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  13. J. Roy, D. Barman, S. Alam, Role of fear in a predator-prey system with ratio-dependent functional response in deterministic and stochastic environment. Biosystems 197, 104176 (2020)

    Article  Google Scholar 

  14. D. Barman, J. Roy, S. Alam, Trade-off between fear level induced by predator and infection rate among prey species. J. Appl. Math. Comput. 64(1), 635–663 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  15. J.P. Gibert, Temperature directly and indirectly influences food web structure. Sci. Rep. 9(1), 5312 (2019)

    Article  ADS  Google Scholar 

  16. U. Daugaard, O.L. Petchey, F. Pennekamp, Warming can destabilize predator-prey interactions by shifting the functional response from type iii to type ii. J. Anim. Ecol. 88(10), 1575–1586 (2019)

    Article  Google Scholar 

  17. D. Barman, J. Roy, S. Alam, Impact of wind in the dynamics of prey-predator interactions. Math. Comput. Simul. 191, 49–81 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  18. D. Barman, V. Kumar, J. Roy, S. Alam, Modeling wind effect and herd behavior in a predator-prey system with spatiotemporal dynamics. Eur. Phys. J. Plus 137(8), 1–28 (2022)

    Article  Google Scholar 

  19. M.J. Bishop, Displacement of epifauna from seagrass blades by boat wake. J. Exp. Mar. Biol. Ecol. 354(1), 111–118 (2008)

    Article  Google Scholar 

  20. F. Gabel, X.-F. Garcia, M. Brauns, A. Sukhodolov, M. Leszinski, M. Pusch, Resistance to ship-induced waves of benthic invertebrates in various littoral habitats. Freshw. Biol. 53(8), 1567–1578 (2008)

    Article  Google Scholar 

  21. C. Wolter, R. Arlinghaus, Navigation impacts on freshwater fish assemblages: the ecological relevance of swimming performance. Rev. Fish Biol. Fish. 13, 63–89 (2003)

    Article  Google Scholar 

  22. C. Wolter, R. Arlinghaus, A. Sukhodolov, C. Engelhardt, A model of navigation-induced currents in inland waterways and implications for juvenile fish displacement. Environ. Manage. 34, 656–668 (2004)

    Article  Google Scholar 

  23. S. Stoll, P. Fischer, Three different patterns of how low-intensity waves can affect the energy budget of littoral fish: a mesocosm study. Oecologia 165, 567–576 (2011)

    Article  ADS  Google Scholar 

  24. D. Smee, Environmental context influences the outcomes of predator-prey interactions and degree of top-down control. Natl. Educ. Knowl. 3, 58 (2012)

    Google Scholar 

  25. E.M. Robinson, D.L. Smee, G.C. Trussell, Green crab (Carcinus maenas) foraging efficiency reduced by fast flows. PLoS ONE 6(6), e21025 (2011)

    Article  ADS  Google Scholar 

  26. T.A. Keller, M.J. Weissburg, Effects of odor flux and pulse rate on chemosensory tracking in turbulent odor plumes by the blue crab, Callinectes sapidus. Biol. Bull. 207(1), 44–55 (2004)

    Article  Google Scholar 

  27. D.L. Smee, M.J. Weissburg, Hard clams (Mercenaria mercenaria) evaluate predation risk using chemical signals from predators and injured conspecifics. J. Chem. Ecol. 32(3), 605–619 (2006)

    Article  Google Scholar 

  28. S.P. Powers, J.N. Kittinger, Hydrodynamic mediation of predator-prey interactions: differential patterns of prey susceptibility and predator success explained by variation in water flow. J. Exp. Mar. Biol. Ecol. 273(2), 171–187 (2002)

    Article  Google Scholar 

  29. D.L. Smee, M.C. Ferner, M.J. Weissburg, Hydrodynamic sensory stressors produce nonlinear predation patterns. Ecology 91(5), 1391–1400 (2010)

    Article  Google Scholar 

  30. J. Gupta, J. Dhar, P. Sinha, An eco-epidemic model with seasonal variability: a non-autonomous model. Arab. J. Math. 11(3), 521–538 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  31. M. Izadi, Ş Yüzbaşı, W. Adel, Accurate and efficient matrix techniques for solving the fractional Lotka–Volterra population model. Physica A 600, 127558 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  32. G.-Q. Sun, Z. Jin, L. Li, Q.-X. Liu, The role of noise in a predator-prey model with Allee effect. J. Biol. Phys. 35, 185–196 (2009)

    Article  Google Scholar 

  33. M. Weissburg, C. James, D. Smee, D. Webster, Fluid mechanics produces conflicting, constraints during olfactory navigation of blue crabs, Callinectes sapidus. J. Exp. Biol. 206(1), 171–180 (2003)

    Article  Google Scholar 

  34. A. S. Purnomo, I. Darti, A. Suryanto, Dynamics of eco-epidemiological model with harvesting, in: AIP Conference Proceedings, Vol. 1913, AIP Publishing LLC, (2017), p. 020018

  35. A. Chatterjee, S. Pal, Switching effects driven by predation on diffusive predator prey system. Appl. Appl. Math. Int. J. (AAM) 16(1), 38 (2021)

    MathSciNet  MATH  Google Scholar 

  36. C. Jørgensen, R.E. Holt, Natural mortality: its ecology, how it shapes fish life histories, and why it may be increased by fishing. J. Sea Res. 75, 8–18 (2013)

    Article  ADS  Google Scholar 

  37. A. Mandal, P.K. Tiwari, S. Samanta, E. Venturino, S. Pal, A nonautonomous model for the effect of environmental toxins on plankton dynamics. Nonlinear Dyn. 99(4), 3373–3405 (2020)

    Article  MATH  Google Scholar 

  38. A. Mandal, P.K. Tiwari, S. Pal, A nonautonomous model for the effects of refuge and additional food on the dynamics of phytoplankton-zooplankton system. Ecol. Complex. 46, 100927 (2021)

    Article  Google Scholar 

  39. S. Biswas, P. Kumar Tiwari, S. Pal, Effects of toxicity and zooplankton selectivity on plankton dynamics under seasonal patterns of viruses with time delay. Math. Methods Appl. Sci. 45(2), 585–617 (2022)

    Article  ADS  MathSciNet  Google Scholar 

  40. S. Biswas, P.K. Tiwari, S. Pal, Delay-induced chaos and its possible control in a seasonally forced eco-epidemiological model with fear effect and predator switching. Nonlinear Dyn. 104(3), 2901–2930 (2021)

    Article  Google Scholar 

  41. F. Chen, On a nonlinear nonautonomous predator-prey model with diffusion and distributed delay. J. Comput. Appl. Math. 180(1), 33–49 (2005)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  42. R.E. Gaines, J.L. Mawhin, Coincidence Degree and Nonlinear Differential Equations, vol. 568 (Springer, Cham, 2006)

    MATH  Google Scholar 

  43. A. Huppert, B. Blasius, R. Olinky, L. Stone, A model for seasonal phytoplankton blooms. J. Theor. Biol. 236(3), 276–290 (2005)

    Article  ADS  MathSciNet  MATH  Google Scholar 

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Contributions

DB: Conceptualization, Formal analysis, Investigation, Software, Writing - original draft. SN: Formal analysis, Investigation, Visualization, Writing - original draft. AM: Methodology, Project administration, Validation, Writing - review & editing. SA: Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing - review & editing.

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Correspondence to Dipesh Barman.

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Barman, D., Naskar, S., Mandal, A. et al. Impact of seasonal variability of sea waves on the dynamics of a predator–prey system. Eur. Phys. J. Plus 138, 641 (2023). https://doi.org/10.1140/epjp/s13360-023-04295-5

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